Modelling and Tools of the Future Miika Alonen, CSC IT Center for - - PowerPoint PPT Presentation

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Modelling and Tools of the Future Miika Alonen, CSC IT Center for - - PowerPoint PPT Presentation

Aug 23, 2023 205 likes •511 views

INTEROPERABILITY + SEMANTICS = CHECK! Smart and Cost Effective Data Modelling and Tools of the Future Miika Alonen, CSC IT Center for Science Suvi Remes, CSC IT Center for Science Patrik Maltusch, Aalto University Mikael af Hllstrm ,

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INTEROPERABILITY + SEMANTICS = CHECK! Smart and Cost Effective Data Modelling and Tools of the Future

Miika Alonen, CSC – IT Center for Science Suvi Remes, CSC – IT Center for Science Patrik Maltusch, Aalto University Mikael af Hällström, Finnish Tax Administration

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Summary

  • Interoperability challenges
  • Interoperability case: Student Transcript
  • Framework for Semantic Interoperability
  • Implementing the Framework:

– Interoperability workbench

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Organisation and application specific documentation Point to point Integration Redefining data models No change management

  • ver organisation borders

Present – Information chaos

VIRTA

Opintopolku Oodi X Vipunen Oili VTJ Y

EMREX

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Interoperability CASE: Student Transcript

4 Your logo here

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1000 h

60.000 € 80 h 4800 €

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Making data sources semantic interoperable for a DW

~80.000 €

~1 milj. €

Cost for the community

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Equation for Interoperability

ICC∗ESB∗EIM∗DW = 𝑐𝑓𝑜𝑓𝑔𝑗𝑢𝑡 𝑑𝑝𝑡𝑢 >1

ICC = Integration Competence Center ESB = Enterprise Service Bus EIM = Enterprise Information Management DW = DataWareHouse

by Patrik Maltusch @aalto.fi

SEMANTIC IMPACT

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Data warehouses

RDB SQL

Reference data

Enumerations XML schema JSON Codeservers

Application interfaces

XML WSDL SOAP

Programming

Java Javascript Swagger Python Terminological dictionaries

Glossary

Wikis Concept models Classifications SKOS

Data modelling

UML XML Wiki Excel RDF ER Documents

Used methods for documenting APIs?

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Application profiles

Uniform documentation for data APIs and Applications

Domain vocabularies

Reusable core data models Reusable classifications

Vision – Data model reuse and uniform documentation

VIRTA

Oili Opintopolku X Y UNI Ö

EMREX

Application profiles Shared semantics Use of shared semantics

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2000 - Idea of Application Profiles evolved from DESIRE Registry project: “mixing and matching” metadata elements 2003 - Guidelines for creating application profiles (CEN/CWA 14855) 2005 – Guidelines for machine- readable representation .. (CEN/CWA 15248) 2006 - Guidelines building application profiles in e-learning (CEN/CWA 15555) 2008 - Guidelines for Dublin Core Application Profiles 2011 - 2016 – MLR Framework (ISO/IEC 19788-1) An Application profile seeks to address the interoperability requirements between systems by:

  • retaining conformance with a

base standard

  • defining new requirements in an
  • pen and interoperable manner

Application profiles

Examples of standard Application profiles: CEN/CWA 15903: Metadata for Learning Opportunities CEN/CWA 16132: European Learner Mobility Achievement Information EMREX AP (2016): Report for the recognition of external studies

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Need for common framework

Shared concepts with the business and IT:

  • 1. Well defined concepts
  • 2. Unique identifiers
  • 3. Machine readable format

Service innovation and data modeling based on business needs:

  • 1. Reuse terms and definitions
  • 2. Create reusable components
  • 3. Focus on the interfaces and

integration Framework for semantic interoperability:

  • How to publish core vocabularies
  • and application profiles?
  • How to reuse standards?
  • How to reuse core vocabularies in

the implementations?

  • How to document the metadata

reuse?

  • How to document application

interfaces?

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Terminology

  • Concepts
  • Definitions
  • Classifications

Core vocabularies

  • Classes
  • Attributes
  • Associations

Application Profiles

  • Context
  • Constraints
  • Extensions

Common metadata architecture for data modelling:

  • Machine readable terminology
  • Reusable core vocabularies and core components
  • Documented reuse of core components

Semantic interoperability framework

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Interoperability objectives

  • Shared metadata

models for education and research

  • Modular and reusable

metadata definitions

  • Improve readability

and understandability

  • f data models
  • Interoperability with

international standards

  • Promote standard

reuse

  • Formal and semantic

mappings to CEN and ISO standards

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Interoperability benefits

  • Collaborative tool for

metadata publishing

– Benefit from external expertice

  • Avoid redefinition of

data models

– Lower integration costs

  • Shared terminology

– Less confusion

  • Same terms for many

communications needs

– Study administration – User interfaces

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Domain specific vocabularies are administered by different agencies and published in the standard SKOS model in the Finnish Thesaurus and Ontology Service

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Core vocabularies are published as Linked Data that defines re-usable classes and properties based on shared concepts and links to standards and best practices.

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Domain specific data models and interfaces are documented as Application profiles that re-use the classes and properties from the Core Vocabularies

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Data models are implemented with languages that best suit the given architecture by implementing the application profile.

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Simplified process for describing Core vocabularies and Application profiles

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Piloting Interoperability Framework

Core vocabularies Application profiles

iow.csc.fi

VIRTA Oili Opintopolku University Information Systems Enables Universities and Consortium Partners to start documenting local implementations using free & open source tools Documenting Open APIs Documenting Open APIs EduCloud EMREX

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Interoperability workbench

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  • Collaborative online tool for creating Core Vocabularies and Application Profiles:
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Interoperability workbnech

  • Tool for defining resolvable and machine readable data models
  • Document the use of data models, standards and best practices
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Integration to controlled vocabularies

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  • Link controlled vocabularies to created model
  • Create classes and properties based on existing concepts
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Integration to classification schemes

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  • Link to existing reference data from code service
  • Restrict allowed values by using existing reference data
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Interoperability workbench

  • Import existing models from local models and external namespaces
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Interoperability workbench

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  • Include and search metadata from imported standards
  • Create new domain models as highly reusable metadata
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Interoperability workbench

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  • Map new classes and class usage to relevant standards
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Interoperability workbench

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RDF XML Schema tbd … JSON Schema

  • Export schemas in multiple formats
  • Enforces Naming practices
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Thanks!

  • Questions
  • Interoperability

workbench

  • http://iow.csc.fi

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